Planarplot-methods

Planarplot,matrix,numeric,missing-method

Planarplot,matrix,factor,missing-method

Planarplot,data.frame,missing,formula-method

Planarplot,ExpressionSet,character,missing-method

Given two variables, the methods trains a classifier
  (argument <code>classifier</code>) based on these two variables
  and plots the resulting class regions, learning- and test
  observations in the plane.<p></p><p>  Appropriate variables are usually found by <code><a rd-options="" href="/link/GeneSelection?package=CMA&version=1.30.0" data-mini-rdoc="CMA::GeneSelection">GeneSelection</a></code>.</p>

multivariate

This package provides a comprehensive collection of various microarray-based classification algorithms
both from Machine Learning and Statistics.
Variable Selection, Hyperparameter tuning, Evaluation and Comparison can be performed
combined or stepwise in a user-friendly environment.

Christoph Bernau

Synthesis of microarray-based classification

Planarplot-methods function

<dl> <dt>X = "matrix", y = "numeric", f = "missing"</dt><dd>signature 1</dd> <dt>X = "matrix", y = "factor", f = "missing"</dt><dd>signature 2</dd> <dt>X = "data.frame", y = "missing", f = "formula"</dt><dd>signature 3</dd> <dt>X = "ExpressionSet", y = "character", f = "missing"</dt><dd>signature 4</dd> </dl> For further argument and output information, consult
<code><a rd-options="" href="/link/Planarplot?package=CMA&version=1.30.0" data-mini-rdoc="CMA::Planarplot">Planarplot</a></code>.

Methods

Given two variables, the methods trains a classifier
  (argument <code>classifier</code>) based on these two variables
  and plots the resulting class regions, learning- and test
  observations in the plane.

  Appropriate variables are usually found by <code><a href="GeneSelection" rd-options="">GeneSelection</a></code>.

Planarplot-methods: Visualize Separability of different classes

Description

Arguments

Methods